code: def soft_input_values():
      values = {
          "y_true": [0, 1, 1, 1, 0, 0, np.nan, np.nan, 0],
          "y_pred": [0, 0, 0, 1, 0, 1, np.nan, 1, np.nan],
          "expected_soft_precision": [
              {0.0: 0.5, 1.0: 0.5},
              {1.0: 0.5, 0.0: 0.0},
              {1.0: 1.0, 0.0: 0.0},
          ],
          "expected_soft_recall": [
              {0.0: 2 / 3, 1.0: 1 / 3},
              {0.0: 1 / 3, 1.0: 2 / 3},
              {0.0: 1 / 3, 1.0: 1.0},
          ],
          "expected_soft_f1": [
              {0.0: 0.5714285714285715, 1.0: 0.4},
              {0.0: 0.0, 1.0: 0.5714285714285715},
              {0.0: 0.0, 1.0: 1.0},
          ],
      }
  
      return values
  
imports: import numpy
  import pandas
  import pytest
  from greykite.detection.common.ad_evaluation import confusion_matrix
  from greykite.detection.common.ad_evaluation import f1_score
  from greykite.detection.common.ad_evaluation import informedness_statistic
  from greykite.detection.common.ad_evaluation import matthews_corrcoef
  from greykite.detection.common.ad_evaluation import precision_score
  from greykite.detection.common.ad_evaluation import range_based_precision_score
  from greykite.detection.common.ad_evaluation import range_based_recall_score
  from greykite.detection.common.ad_evaluation import recall_score
  from greykite.detection.common.ad_evaluation import soft_f1_score
  from greykite.detection.common.ad_evaluation import soft_precision_score
  from greykite.detection.common.ad_evaluation import soft_recall_score
label_desc: Use image node_id 2 for calling a global function with example usage: soft_input_values() and returns: values